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Issue No.05 - September/October (2011 vol.8)
pp: 1344-1357
Peter Boyen , Hasselt University, Diepenbeek and Transnational University of Limburg
Dries Van Dyck , Hasselt University, Diepenbeek and Transnational University of Limburg
Frank Neven , Hasselt University, Diepenbeek and Transnational University of Limburg
Roeland C.H.J. van Ham , Applied Bioinformatics - Plant Research International, Wageningen
Aalt D.J. van Dijk , Applied Bioinformatics - Plant Research International, Wageningen
Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on
Graphs and networks, biology and genetics.
Peter Boyen, Dries Van Dyck, Frank Neven, Roeland C.H.J. van Ham, Aalt D.J. van Dijk, "SLIDER: A Generic Metaheuristic for the Discovery of Correlated Motifs in Protein-Protein Interaction Networks", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.8, no. 5, pp. 1344-1357, September/October 2011, doi:10.1109/TCBB.2011.17
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